Package: mclust 6.1.1

mclust: Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimation

Gaussian finite mixture models fitted via EM algorithm for model-based clustering, classification, and density estimation, including Bayesian regularization, dimension reduction for visualisation, and resampling-based inference.

Authors:Chris Fraley [aut], Adrian E. Raftery [aut], Luca Scrucca [aut, cre], Thomas Brendan Murphy [ctb], Michael Fop [ctb]

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NEWS

# Install 'mclust' in R:
install.packages('mclust', repos = c('https://luca-scr.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/mclust-org/mclust/issues

Uses libs:
  • openblas– Optimized BLAS
Datasets:
  • EuroUnemployment - Unemployment data for European countries in 2014
  • GvHD.control - GvHD Dataset
  • GvHD.pos - GvHD Dataset
  • Test1D - Simulated Example Datasets From Baudry et al.
  • acidity - Acidity data
  • banknote - Swiss banknotes data
  • chevron - Simulated minefield data
  • cross - Simulated Cross Data
  • diabetes - Diabetes Data
  • ex4.1 - Simulated Example Datasets From Baudry et al.
  • ex4.2 - Simulated Example Datasets From Baudry et al.
  • ex4.3 - Simulated Example Datasets From Baudry et al.
  • ex4.4.1 - Simulated Example Datasets From Baudry et al.
  • ex4.4.2 - Simulated Example Datasets From Baudry et al.
  • thyroid - UCI Thyroid Gland Data
  • wdbc - UCI Wisconsin Diagnostic Breast Cancer Data
  • wreath - Data Simulated from a 14-Component Mixture

On CRAN:

280 exports 20 stars 12.55 score 0 dependencies 573 dependents 297 mentions 6.0k scripts 57.2k downloads

Last updated 6 months agofrom:65e2a1c053. Checks:OK: 9. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 20 2024
R-4.5-win-x86_64OKSep 20 2024
R-4.5-linux-x86_64OKSep 20 2024
R-4.4-win-x86_64OKSep 20 2024
R-4.4-mac-x86_64OKSep 20 2024
R-4.4-mac-aarch64OKSep 20 2024
R-4.3-win-x86_64OKSep 20 2024
R-4.3-mac-x86_64OKSep 20 2024
R-4.3-mac-aarch64OKSep 20 2024

Exports:adjustedRandIndexas.densityMclustas.densityMclust.defaultas.densityMclust.Mclustas.hclust.hcas.Mclustas.Mclust.defaultas.Mclust.densityMclustbicbicEMtrainBrierScorecdenscdensEcdensEEEcdensEEIcdensEEVcdensEIIcdensEVEcdensEVIcdensEVVcdensVcdensVEEcdensVEIcdensVEVcdensVIIcdensVVEcdensVVIcdensVVVcdensXcdensXIIcdensXXIcdensXXXcdfMclustcheckModelNameclassErrorclassPriorProbsclPairsclPairsLegendclustCombiclustCombiOptimcombiPlotcombiTreecombMatcoordProjcovwcrimcoordscv.MclustDAcv1EMtraincvMclustDAdecomp2sigmadefaultPriordensdensityMclustdensityMclust.diagnosticdmvnormdupPartitionememControlemEemEEEemEEIemEEVemEIIemEVEemEVIemEVVemVemVEEemVEIemVEVemVIIemVVEemVVIemVVVemXemXIIemXXIemXXXentPloterrorBarsestepestepEestepEEEestepEEIestepEEVestepEIIestepEVEestepEVIestepEVVestepVestepVEEestepVEIestepVEVestepVIIestepVVEestepVVIestepVVVgetParameters.MclustDAgmmhdgmmhdClassifygmmhdClusterCoreshchcEhcEEEhcEIIhclasshcRandomPairshcVhcVIIhcVVVhdrlevelshypvoliclimputeDataimputePairslogLik.MclustlogLik.MclustDAlogsumexpmajorityVotemapmapClassmatchClusterMclustmclust.optionsmclust1Dplotmclust2DplotmclustBICmclustBICupdateMclustBootstrapmclustBootstrapLRTMclustDAMclustDRMclustDRrecoverdirMclustDRsubselMclustDRsubsel_classifMclustDRsubsel_clusterMclustDRsubsel1cyclemclustICLmclustLoglikmclustModelmclustModelNamesMclustSSCmclustVariancememe.weightedmeEmeEEEmeEEImeEEVmeEIImeEVEmeEVImeEVVmeVmeVEEmeVEImeVEVmeVIImeVVEmeVVImeVVVmeXmeXIImeXXImeXXXmstepmstepEmstepEEEmstepEEImstepEEVmstepEIImstepEVEmstepEVImstepEVVmstepVmstepVEEmstepVEImstepVEVmstepVIImstepVVEmstepVVImstepVVVmvnmvn2plotmvnXmvnXIImvnXXImvnXXXnMclustParamsnVarParamspartconvpartuniqpickBICplot.clustCombiplot.crimcoordsplot.densityMclustplot.gmmhdplot.hcplot.Mclustplot.mclustBICplot.MclustBootstrapplot.mclustBootstrapLRTplot.MclustDAplot.MclustDRplot.mclustICLplot.MclustSSCplotDensityMclust1plotDensityMclust2plotDensityMclustdplotEvalues.MclustDRpredict.densityMclustpredict.Mclustpredict.MclustDApredict.MclustDRpredict.MclustSSCpredict2D.MclustDRprint.clustCombiprint.crimcoordsprint.gmmhdprint.hcprint.Mclustprint.mclustBICprint.MclustBootstrapprint.mclustBootstrapLRTprint.MclustDAprint.MclustDRprint.MclustDRsubselprint.mclustICLprint.mclustLoglikprint.MclustSSCprint.summary.clustCombiprint.summary.crimcoordsprint.summary.gmmhdprint.summary.Mclustprint.summary.MclustBootstrapprint.summary.MclustDAprint.summary.MclustDRprint.summary.mclustICLprint.summary.MclustSSCpriorControlprojpar.MclustDRquantileMclustrandomOrthogonalMatrixrandomPairsrandProjsigma2decompsimsimEsimEEEsimEEIsimEEVsimEIIsimEVEsimEVIsimEVVsimVsimVEEsimVEIsimVEVsimVIIsimVVEsimVVIsimVVVsoftmaxsummary.clustCombisummary.crimcoordssummary.gmmhdsummary.Mclustsummary.mclustBICsummary.MclustBootstrapsummary.MclustDAsummary.MclustDRsummary.MclustDRsubselsummary.mclustICLsummary.MclustSSCsummaryMclustBICsummaryMclustBICnsurfacePlotuncerPlotunmap

Dependencies:

A quick tour of mclust

Rendered frommclust.Rmdusingknitr::rmarkdownon Sep 20 2024.

Last update: 2023-11-17
Started: 2015-04-01

Readme and manuals

Help Manual

Help pageTopics
Gaussian Mixture Modelling for Model-Based Clustering, Classification, and Density Estimationmclust-package mclust
Acidity dataacidity
Adjusted Rand IndexadjustedRandIndex
Swiss banknotes databanknote
Simulated Example Datasets From Baudry et al. (2010)Baudry_etal_2010_JCGS_examples ex4.1 ex4.2 ex4.3 ex4.4.1 ex4.4.2 Test1D
BIC for Parameterized Gaussian Mixture Modelsbic
Brier score to assess the accuracy of probabilistic predictionsBrierScore
Component Density for Parameterized MVN Mixture Modelscdens
Component Density for a Parameterized MVN Mixture ModelcdensE cdensEEE cdensEEI cdensEEV cdensEII cdensEVE cdensEVI cdensEVV cdensV cdensVEE cdensVEI cdensVEV cdensVII cdensVVE cdensVVI cdensVVV cdensX cdensXII cdensXXI cdensXXX
Cumulative Distribution and Quantiles for a univariate Gaussian mixture distributioncdfMclust quantileMclust
Simulated minefield datachevron
Classification errorclassError
Estimation of class prior probabilities by EM algorithmclassPriorProbs
Pairwise Scatter Plots showing ClassificationclPairs clPairsLegend
Combining Gaussian Mixture Components for ClusteringclustCombi print.clustCombi print.summary.clustCombi summary.clustCombi
Optimal number of clusters obtained by combining mixture componentsclustCombiOptim
Plot Classifications Corresponding to Successive Combined SolutionscombiPlot
Tree structure obtained from combining mixture componentscombiTree
Combining MatrixcombMat
Coordinate projections of multidimensional data modeled by an MVN mixture.coordProj
Weighted means, covariance and scattering matrices conditioning on a weighted matrixcovw
Discriminant coordinates data projectioncrimcoords plot.crimcoords print.crimcoords print.summary.crimcoords summary.crimcoords
Simulated Cross Datacross
MclustDA cross-validationcvMclustDA
Convert mixture component covariances to matrix formdecomp2sigma
Default conjugate prior for Gaussian mixturesdefaultPrior
Density for Parameterized MVN Mixturesdens
Density Estimation via Model-Based ClusteringdensityMclust
Diagnostic plots for 'mclustDensity' estimationdensityMclust.diagnostic
Diabetes Data (flawed)diabetes
Density of multivariate Gaussian distributiondmvnorm
Partition the data by grouping together duplicated datadupPartition
EM algorithm starting with E-step for parameterized Gaussian mixture modelsem
Set control values for use with the EM algorithmemControl
EM algorithm starting with E-step for a parameterized Gaussian mixture modelemE emEEE emEEI emEEV emEII emEVE emEVI emEVV emV emVEE emVEI emVEV emVII emVVE emVVI emVVV emX emXII emXXI emXXX
Plot Entropy PlotsentPlot
Draw error bars on a ploterrorBars
E-step for parameterized Gaussian mixture models.estep
E-step in the EM algorithm for a parameterized Gaussian mixture model.estepE estepEEE estepEEI estepEEV estepEII estepEVE estepEVI estepEVV estepV estepVEE estepVEI estepVEV estepVII estepVVE estepVVI estepVVV
Unemployment data for European countries in 2014EuroUnemployment
Identifying Connected Components in Gaussian Finite Mixture Models for Clusteringgmmhd gmmhdClassify gmmhdClusterCores plot.gmmhd print.gmmhd print.summary.gmmhd summary.gmmhd
GvHD DatasetGvHD GvHD.control GvHD.pos
Model-based Agglomerative Hierarchical Clusteringas.hclust.hc hc print.hc
Model-based Hierarchical ClusteringhcE hcEEE hcEII hcV hcVII hcVVV
Classifications from Hierarchical Agglomerationhclass
Random hierarchical structurehcRandomPairs randomPairs
Highest Density Region (HDR) Levelshdrlevels
Aproximate Hypervolume for Multivariate Datahypvol
ICL for an estimated Gaussian Mixture Modelicl
Missing data imputation via the 'mix' packageimputeData matchCluster
Pairwise Scatter Plots showing Missing Data ImputationsimputePairs
Log-Likelihood of a 'Mclust' objectlogLik.Mclust
Log-Likelihood of a 'MclustDA' objectlogLik.MclustDA
Log sum of exponentialslogsumexp
Majority votemajorityVote
Classification given Probabilitiesmap
Correspondence between classificationsmapClass
Model-Based ClusteringMclust print.Mclust
Deprecated Functions in mclust packagebicEMtrain cv.MclustDA cv1EMtrain
Default values for use with MCLUST packagemclust.options
Plot one-dimensional data modeled by an MVN mixture.mclust1Dplot
Plot two-dimensional data modelled by an MVN mixturemclust2Dplot
BIC for Model-Based ClusteringEMclust mclustBIC print.mclustBIC
Update BIC values for parameterized Gaussian mixture modelsmclustBICupdate
Resampling-based Inference for Gaussian finite mixture modelsMclustBootstrap print.MclustBootstrap
Bootstrap Likelihood Ratio Test for the Number of Mixture ComponentsmclustBootstrapLRT plot.mclustBootstrapLRT print.mclustBootstrapLRT
MclustDA discriminant analysisMclustDA print.MclustDA
Dimension reduction for model-based clustering and classificationMclustDR print.MclustDR
Subset selection for GMMDR directions based on BICMclustDRrecoverdir MclustDRsubsel MclustDRsubsel1cycle MclustDRsubsel_classif MclustDRsubsel_cluster print.MclustDRsubsel summary.MclustDRsubsel
ICL Criterion for Model-Based ClusteringmclustICL print.mclustICL print.summary.mclustICL summary.mclustICL
Log-likelihood from a table of BIC values for parameterized Gaussian mixture modelsmclustLoglik print.mclustLoglik
Best model based on BICmclustModel
MCLUST Model NamesmclustModelNames
MclustSSC semi-supervised classificationMclustSSC print.MclustSSC
Template for variance specification for parameterized Gaussian mixture modelsmclustVariance
EM algorithm starting with M-step for parameterized MVN mixture modelsme
EM algorithm with weights starting with M-step for parameterized Gaussian mixture modelsme.weighted
EM algorithm starting with M-step for a parameterized Gaussian mixture modelmeE meEEE meEEI meEEV meEII meEVE meEVI meEVV meV meVEE meVEI meVEV meVII meVVE meVVI meVVV meX meXII meXXI meXXX
M-step for parameterized Gaussian mixture modelsmstep
M-step for a parameterized Gaussian mixture modelmstepE mstepEEE mstepEEI mstepEEV mstepEII mstepEVE mstepEVI mstepEVV mstepV mstepVEE mstepVEI mstepVEV mstepVII mstepVVE mstepVVI mstepVVV
Univariate or Multivariate Normal Fitmvn
Univariate or Multivariate Normal FitmvnX mvnXII mvnXXI mvnXXX
Number of Estimated Parameters in Gaussian Mixture ModelsnMclustParams
Number of Variance Parameters in Gaussian Mixture ModelsnVarParams
Numeric Encoding of a Partitioningpartconv
Classifies Data According to Unique Observationspartuniq
Plot Combined Clusterings Resultsplot.clustCombi
Plots for Mixture-Based Density Estimateplot.densityMclust plotDensityMclust1 plotDensityMclust2 plotDensityMclustd
Dendrograms for Model-based Agglomerative Hierarchical Clusteringplot.hc
Plotting method for Mclust model-based clusteringplot.Mclust
BIC Plot for Model-Based Clusteringplot.mclustBIC
Plot of bootstrap distributions for mixture model parametersplot.MclustBootstrap
Plotting method for MclustDA discriminant analysisplot.MclustDA
Plotting method for dimension reduction for model-based clustering and classificationplot.MclustDR plotEvalues.MclustDR
ICL Plot for Model-Based Clusteringplot.mclustICL
Plotting method for MclustSSC semi-supervised classificationplot.MclustSSC
Density estimate of multivariate observations by Gaussian finite mixture modelingpredict.densityMclust
Cluster multivariate observations by Gaussian finite mixture modelingpredict.Mclust
Classify multivariate observations by Gaussian finite mixture modelingpredict.MclustDA
Classify multivariate observations on a dimension reduced subspace by Gaussian finite mixture modelingpredict.MclustDR predict2D.MclustDR
Classification of multivariate observations by semi-supervised Gaussian finite mixturespredict.MclustSSC
Conjugate Prior for Gaussian Mixtures.priorControl
Random orthogonal matrixrandomOrthogonalMatrix
Random projections of multidimensional data modeled by an MVN mixturerandProj
Convert mixture component covariances to decomposition form.sigma2decomp
Simulate from Parameterized MVN Mixture Modelssim
Simulate from a Parameterized MVN Mixture ModelsimE simEEE simEEI simEEV simEII simEVE simEVI simEVV simV simVEE simVEI simVEV simVII simVVE simVVI simVVV
Softmax functionsoftmax
Summarizing Gaussian Finite Mixture Model Fitsprint.summary.Mclust summary.Mclust
Summary function for model-based clustering via BICprint.summary.mclustBIC printSummaryMclustBIC printSummaryMclustBICn summary.mclustBIC summaryMclustBIC summaryMclustBICn
Summary Function for Bootstrap Inference for Gaussian Finite Mixture Modelsprint.summary.MclustBootstrap summary.MclustBootstrap
Summarizing discriminant analysis based on Gaussian finite mixture modelingprint.summary.MclustDA summary.MclustDA
Summarizing dimension reduction method for model-based clustering and classificationprint.summary.MclustDR summary.MclustDR
Summarizing semi-supervised classification model based on Gaussian finite mixturesprint.summary.MclustSSC summary.MclustSSC
Density or uncertainty surface for bivariate mixturessurfacePlot
UCI Thyroid Gland Datathyroid
Uncertainty Plot for Model-Based ClusteringuncerPlot
Indicator Variables given Classificationunmap
UCI Wisconsin Diagnostic Breast Cancer Datawdbc
Data Simulated from a 14-Component Mixturewreath